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Field
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opportunity to learn from our highly interdisciplinary, collaborative, and dynamic research group that meets regularly and includes leading scientists (and other fellows) with expertise in several disciplines
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statistical methods, computational models and/ or machine learning algorithms to analyse environmental and infectious disease data; - Collaborate with multidisciplinary and international teams of researchers
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Experience in working with fish tracking systems and machine learning models Experience with commercial on on-farm field data collection in aquaculture settings Experience in oral presentations for conferences
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We invite excellent candidates in classical machine learning to join a collaborative research initiative between the MathEXLab of NUS (Mechanical Engineering) and the Centre for Quantum Technologies
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artificial intelligence and machine learning (AI/ML) models that predict therapeutic response, identify clinically actionable patient subgroups, and support personalized treatment strategies. Through
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skills, including statistical analysis using R, Python, SPSS, Stata, or equivalent software. • Experience with computational social science methods, including NLP, machine learning, LLMs, social media
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will contribute to all stages of the research process, including literature review, conceptual framework development, data collection and preparation, AI and machine learning model development
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biology, machine learning, and predictive modelling; translational studies integrating laboratory discoveries with clinical implementation. Vancouver is a vibrant coastal city located on the traditional
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Architecture: Architect, build, and evaluate multi-agent systems powered by LLMs and machine learning, incorporating Orchestrator and Memory agents, vector databases, and knowledge graphs to enable complex goal
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adaptive cybersecurity solutions for shared social and economic systems. The successful researcher will apply expertise in programmable networking, network traffic analysis, and machine-learning